鄂尔多斯盆地煤层气甜点地震预测技术与工程应用OA

[Objective]Deep coalbed methane(CBM)reservoirs tend to exhibit significant tuning effects of thin inter-beds,leading to challenging localization of actual coal seam boundaries,limited identification accuracy of micro-amp-litude structures in the coal seam roof,and poor stability of the seismic responses of the reservoirs' gas-bearing proper-ties.To address these challenges,this study investigated the No.8 coal seam of the Benxi Formation in the Mizhi area,Ordos Basin.Accordingly,a method with the prediction of gas-bearing properties as the primary controlling factor was developed for the seismic prediction and comprehensive evaluation of CBM sweet spots.[Methods]First,the actual roof boundaries of the No.8 coal seam were traced using high-resolution reflection coefficient volumes,and low-amp-litude microstructures in the coal seam roof were characterized through detrending.Then,the thin coal seam thicknesses and roof lithologies were predicted through facies-controlled geostatistical inversion.Based on core experiments and the crossplot analysis of log parameters,the product of Lamé constant λ and density ρ(λρ)was preferentially selected as a seismic parameter for indicating the gas-bearing properties of the coal seam.The spatial distribution of gas content in the coal seam was derived through pre-stack elastic inversion.Furthermore,in combination with fracture prediction based on wide-azimuth anisotropic inversion,the evaluation based on multi-parameter fusion including coal seam thickness,roof lithology,microstructures,gas-bearing property,and fractures was achieved using principal component analysis and a two-dimensional convolutional neural network(PCA—2D-CNN).[Results]Interpretations based on reflection coeffi-cient volumes effectively reduced the localization errors induced by the tuning effects of thin interbeds.The coal seam thicknesses of approximately 4 m and above and roof lithologies were effectively predicted,with the λρ-based predic-tion results highly consistent with the measured gas content in wells.Comprehensive evaluation results indicate that classes Ⅰ and Ⅱ CBM play fairways are primarily distributed as NE-trending bands.Given the incomplete nature of exist-ing fracturing data,this study developed a semi-quantitative engineering verification framework involving spatial super-position,fracturing response indicators,and consistent discrimination.[Conclusion]Using λρ-based prediction of gas-bearing properties as the primary controlling factor,the seismic evaluation workflow that integrates constraints from coal seam thicknesses,roof lithologies,microstructures,and fractures can enhance the stability of sweet spot identification in deep-seated thin coal seams.Furthermore,the evaluation workflow can also provide a basis for the selection of optimal play fairways,arrangement of fracturing intervals in wells,and the verification of subsequent fracturing engineering.